Yinan Wang
Assistant Professor in the Department of Industrial and Systems Engineering
Rensselaer Polytechnic Institute
Biography
Dr. Yinan Wang serves as the tenure-track assistant professor in the Department of Industrial and Systems Engineering at Rensselaer Polytechnic Institute. He received the Ph.D. degree in the Grado Department of Industrial and Systems Engineering at Virginia Tech under the supervison of Dr. Xiaowei Yue. His research interest lies in developing systematic engineering-driven machine learning methodologies with applications to advanced manufacturing.
Download his resumé.
For current undergraduate and graduate students at RPI, if you are interested to work with me on the cutting-edge ML/DL/RL projects, please feel free to send me an email or stop by my office at CII 5213.
Interests
- Artificial Intelligence
- Advanced Manufacturing
- System Intelligence
- Machine Learning
- Deep Learning
Education
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PhD in Industrial and Systems Engineering, 2022
Virginia Tech
-
Master in Electrical Engineering, 2019
Columbia University
-
Bachelor in Electrical Engineering and Automation, 2017
Xi'an Jiaotong University
Selected Awards and Honors
- Panel Fellow, NSF CMMI Game Changer Academy (2022-2023)
- FTC Early Career Grant, ASQ (2022)
- Robert J. Lyman Award, PCI (2022)
- Best Ph.D. Dissertation Award, CIE Division, ASME (2022)
- Best Track Paper Award, DAIS Division, IISE (2022)
- Mary G. and Joseph Natrella Scholarship, ASA (2022)
- Featured Article in ISE Magazine, IISE (2022)
- Paul E. Torgersen Graduate Student Research Excellence Award, Virginia Tech, Finalist (2022)
- Best Student Paper Award, SPES + Q&P Divisions, ASA, Winner (2022)
- Best Theoretical Paper Award, INFORMS 2021 Data Mining and Decision Analytics Workshop, Winner (2021)
- Best Student Paper Award, INFORMS 2021 Quality, Statistic and Reliability Section, Finalist (2021)
News
- Oct. 2022: Yinan is selected as the Panel Fellow in the 2023 cohort of the National Science Foundation (NSF) Division of CMMI Game Changer Academies for Advancing Research Innovation (CGCA). Congratulations!
- Oct. 2022: Yinan is selected as the recipient of the Fall Technical Conference Early Career Grant Award from the American Society of Quality (ASQ). Congratulations!
- Aug. 2022: Our paper “Structured-Light Three-Dimensional Scanning for Process Monitoring and Quality Control in Precast Concrete Production” won the Robert J. Lyman Award from Precast/Prestressed Concrete Institute. Congratulations!
- Aug. 2022: Yinan is selected as the recipient of the Best Ph.D. Dissertation Award from Computer and Information in Engineering (CIE) division at ASME. Congratulations!
- May 2022: Our paper “WOOD: Wasserstein-based Out-of-Distribution Detection” won the Best Track Paper Award from Data Analytics and Information System (DAIS) Division at IISE. Congratulations!
- Apr. 2022: Yinan is selected as the finalist of the 2022 Paul E. Torgersen Graduate Student Research Excellence Award, the winner will be further informed in May. Congratulations!
- Apr. 2022: Yinan is selected as the recipient of Mary G. and Joseph Natrella Scholarship from ASA (American Statistical Association). He is also invited to give a presentation at Quality and Productivity Research Conference 2022. We thank the support from ASA!
Experience
Assistant Professor
Rensselaer Polytechnic Institute
Graduate Research Assitant
Virginia Tech
Summer Research Intern
Lawrence Livermore National Lab
Summer Research Intern
Los Alamos National Lab
Recent Publications
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(2022).
Coverage Path Planning for Robotic Quality Inspection with Control on Measurement Uncertainty.
IEEE/ASME Transactions on Mechatronics.
(2021).
Structured-light three-dimensional scanning for process monitoring and quality control in precast concrete production..
PCI Journal.
(2021).
Multiphysics modeling and uncertainty quantification of tribocorrosion in aluminum alloys.
Corrosion Science.
(2021).
NP-ODE: Neural process aided ordinary differential equations for uncertainty quantification of finite element analysis.
IISE Transactions.
(2021).
Tensor decomposition to compress convolutional layers in deep learning.
IISE Transactions.
Publications (Under Review)
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(2022).
ST-GasNet: Spatiotemporal Prediction of Atmospheric Dispersion Clouds using Deep Learning.
IEEE Transactions on Neural Networks and Learning Systems (under review).
(2022).
MVGCN: Multi-view Graph Convolutional Neural Network for Surface Defect Identification using 3D Point Cloud.
ASME Transactions, Journal of Manufacturing Science and Engineering (revision submitted).
(2022).
WOOD: Wasserstein-based Out-of-Distribution Detection.
IEEE Transactions on Pattern Analysis and Machine Intelligence (under review).